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A Bivariate Fractional Probit Model
2018This paper develops a bivariate fractional probit model for fractional response variables, i.e., variables bounded between zero and one. The model can be applied when there are two seemingly unrelated fractional response variables. Since the model relies on a quite strong bivariate normality assumption, specification tests are discussed and the ...
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Selection-endogenous ordered probit and dynamic ordered probit models [PDF]
, 2009 In this presentation we define two qualitatitive response models: 1) Selection Endogenous Dummy Ordered Probit model (SED-OP); 2) a Selection Endogenous Dummy Dynamic Selection Ordered Probit model (SED- DOP). The SED-OP model is a three-equation model constituted of an endogenous dummy equation, a selection equation, and a main equation which has an ...
Alfonso Miranda, Massimiliano Bratti
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Skew-probit measurement error models
Statistical Methodology, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bolfarine, Heleno, Lachos, V. H.
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Probit and Logit Model Selection
Communications in Statistics - Theory and Methods, 2010Monte Carlo experiments are conducted to compare the Bayesian and sample theory model selection criteria in choosing the univariate probit and logit models. We use five criteria: the deviance information criterion (DIC), predictive deviance information criterion (PDIC), Akaike information criterion (AIC), weighted, and unweighted sums of squared errors.
Guo Chen, Hiroki Tsurumi
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1992
Statistical models in which the endogenous random variables take only discrete values are known as discrete, categorical, qualitative — choice, or quanta! response models.1 This class of models was originally developed by psychologists and later adapted and extended by economists for describing consumers choices. These models have numerous applications
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Statistical models in which the endogenous random variables take only discrete values are known as discrete, categorical, qualitative — choice, or quanta! response models.1 This class of models was originally developed by psychologists and later adapted and extended by economists for describing consumers choices. These models have numerous applications
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Reconsidering the multinomial probit model
Transportation Research Part B: Methodological, 1991Recently developed computational methods have greatly reduced the difficulty of estimating multinomial probit models and may soon make multinomial probit a computationally feasible option in applied travel demand modeling. This paper discusses some of the benefits and costs that are associated with the use of multinomial probit in demand modeling.
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Estimating the Correlation in Censored Probit Models
The Review of Economics and Statistics, 1996The estimation of censored probit models can result in an estimated correlation between the disturbances approaching [plus]1.0 or -1.0 when most of the observations are selected into the sample and the outcomes are unequally distributed. Outcomes of 0 can induce an estimated correlation of -1.0, and outcomes of 1 can induce an estimated correlation of [
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Specification Error in Probit Models
The Review of Economics and Statistics, 1985Yatchew, Adonis, Griliches, Zvi
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